Physics‐encoded transfer learning for scale‐up modeling of CHO cell bioreactors
AIChE Journal, EarlyView.Abstract Developing reliable predictive models for mammalian cell bioreactors, particularly Chinese hamster ovary (CHO) cultures widely used in biopharmaceutical manufacturing, remains challenging due to severe data scarcity in industrial‐scale reactors.
Muyang Li, Ming Xiao, Zhe Wu
wiley +1 more source
Bayesian statistics: relevant for the brain? [PDF]
Curr Opin Neurobiol, 2014 Kording KP.
europepmc +1 more source
Advanced Intelligent Discovery, EarlyView.A sequential deep learning framework is developed to model surface roughness progression in multi‐stage microneedle fabrication. Using real‐world experimental data from 3D printing, molding, and casting stages, an long short‐term memory‐based recurrent neural network captures the cumulative influence of geometric parameters and intermediate outputs ...
Abdollah Ahmadpour +5 more
wiley +1 more source
Exploring Spatial Trends and Influencing Factors for Gastric Cancer Based on Bayesian Statistics: A Case Study of Shanxi, China. [PDF]
Int J Environ Res Public Health, 2018 Zhang G, Li J, Li S, Wang Y.
europepmc +1 more source
The Necessity of Dynamic Workflow Managers for Advancing Self‐Driving Labs and Optimizers
Advanced Intelligent Discovery, EarlyView.We assess the maturity and integration readiness of key methodologies for Materials Acceleration Platforms, highlighting the need for dynamic workflow managers. Demonstrating this, we integrate PerQueue into a color‐mixing robot, showing how flexible orchestration improves coordination and optimization.
Simon K. Steensen +6 more
wiley +1 more source
Improved Method for Determining Absolute Phosphorylation Stoichiometry Using Bayesian Statistics and Isobaric Labeling. [PDF]
J Proteome Res, 2017 Lim MY, O'Brien J, Paulo JA, Gygi SP.
europepmc +1 more source
Topology‐Aware Machine Learning for High‐Throughput Screening of MOFs in C8 Aromatic Separation
Advanced Intelligent Discovery, EarlyView.We screened 15,335 Computation‐Ready, Experimental Metal–Organic Frameworks (CoRE‐MOFs) using a topology‐aware machine learning (ML) model that integrates structural, chemical, pore‐size, and topological descriptors. Top‐performing MOFs exhibit aromatic‐enriched cavities and open metal sites that enable π–π and C–H···π interactions, serving as ...
Yu Li, Honglin Li, Jialu Li, Wan‐Lu Li
wiley +1 more source
Using Bayesian statistics to estimate the likelihood a new trial will demonstrate the efficacy of a new treatment. [PDF]
BMC Med Res Methodol, 2017 Biau DJ +5 more
europepmc +1 more source
Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook
Advanced Intelligent Discovery, EarlyView.Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang +4 more
wiley +1 more source
Bayesian statistics and clinical trial designs for human cells and tissue products for regulatory approval. [PDF]
Regen Ther, 2016 Jokura Y, Yano K, Watanabe N, Yamato M.
europepmc +1 more source